Chapter 13 Water Quality Monitoring Networks

204 CHAPTER 13

WATER

QUALITY MON I TOR I NG NETWORKS i Y

Colorado State U ive

b y Thomas G. Sanders,

NECESS I T Y FOR NETWORKS Environmental

legislation

been responsible f o r recent streams.

Such m o n i t o r i n g

and

general

water

quality

awareness

have

increased m o n i t o r i n g a n d s a m p l i n g of water and

testing

can

be expensive

and

a

in

scientific

approach to m i n i m i z i n g costs w h i l s t m a x i m i z i n g b e n e f i t s i s d e s i r a b l e . The

assumption

trends

in

water

that

a

quality,

measure ambient

water

monitoring

actively

guide

implemented,

in

government's

however,

feasibi I i t y

obtaining

conclusive

compromises a n d

compliance etc.,

is

with

water

water

legal

the

view

being

is

the

of

more

which

to

When from

a

in

involved

resources force

of

for

water

efforts.

viewed

available

and

generated

problems

the consequences

detect

legislation

management

is,

can

standards,

into

The

monitoring

That

information w i t h measures,

stream

information

quality

quality

network

incorporated

conclusive

stand-point.

half

monitoring

the U n i t e d States.

envisages

technical

quality

check

quality,

water q u a l i t y management qua1 i t y

water

many

a r e often

not

f u l l y understood. Monitoring conducted

over

necessarily Simply

performed large

hydrologic

collecting

problem; cases, samples

or

ultimate

of

geographic

in

i n fact,

thought types

use

government

is

that

of

data

the

data.

(defined

covering

such

given

agencies

areas

boundaries)

samples

so major,

little

by

a

by

the

analysis

many

political

often

i t becomes a n end to

in

in

techniques

Consequently,

the

to

be

majority

a

used of

major

In many

itself. of

not

streams.

becomes

representativeness

cases,

and

k i lometres of

many

situation

is,

the

or

water

even

the

resources

are

devoted to c o l l e c t i n g d a t a as i t i s the most immediate problem. By

using

most

resources

to

physically

collect

water

resources a r e l e f t to consider the representativeness of a n d space,

d a t a a n a l y s i s o r d a t a use.

m o n i t o r i n g system system

should

be

should

therefore

examined

and

samples,

the sample

little i n time

A b a l a n c e d ( c o l l e c t i o n versus

be developed designed

so

use)

the e n t i r e m o n i t o r i n g

simultaneously

(a

systems

the

system

approach). The purpose of

t h i s chapter

i s to

review

monitoring

and

then d e l i n e a t e the impacts t h a t such a systems a p p r o a c h of m o n i t o r i n g w i l l h a v e on network design b y c o n s i d e r i n g the w a t e r q u a l i t y

v a r i a b l e s to

be

205 monitored,

the sampling location a n d s a m p l i n g frequency.

MONITORING SYSTEM FRAMEWORK

Before

a

monitoring

network

can

be

m o n i t o r i n g program should be delineated, I n addition,

the decisions

designed

the

goals

of

the

and specific objectives applied.

to be made based

upon

information

network and the subsequent actions should also be well

from

the

developed p r i o r to

the collection o r a s i n g l e b i t of data. The a c t u a l

operation

of

a m o n i t o r i n g system can

be

categorized

into

f i v e major functions:

1.

Sample Collection

2.

Laboratory Analysis

3.

Data H a n d l i n g

4.

Data A n a l y s i s

5.

I nformation U t i I i z a t i o n These f i v e functions serve as

quality

conditions

of

water

management

agency

approvals,

regulations,

qua1 i t y . effects

Without of

those

a

the feedback

quality

loop from

management

i s c o n s t a n t l y m a k i n g decisions pollution

monitoring

decisions,

abatement,

feedback

the

loop

(e.g.

etc.)

past

water

making.

r e l a t i v e to

that

accurately

management's

in-stream

decision

affect

and

site

water

documenting

success

A

the

future

direction are uncertain. M o n i t o r i n g network design operational collection

i s an o v e r r i d i n g a c t i v i t y

f u n c t i o n s l i s t e d above) (e.g.

location

that

a n d frequency)

should c a r e f u l l y with

used to o b t a i n the i n f o r m a t i o n r e q u i r e d a n d making.

Thus,

the

type

actually

( c o v e r i n g the f i v e i n t e g r a t e sample of

data

utilized

analysis

in decision

the design of water q u a l i t y m o n i t o r i n g networks must

i n t o account the decision m a k i n g process,

take

the t y p e and level o f s t a t i s t i c a l

a n a l y s i s a p p l i e d to the d a t a , a n d u l t i m a t e use of the d a t a collected. FACTORS I N NETWORK DESIGN M o n i t o r i n g network

design,

guides m o n i t o r i n g operations,

as a p l a n n i n g / d e s i g n can

i t s e l f be broken

componen ts:

1.

Selection of Water Q u a l i t y V a r i a b l e s to Monitor

2.

Sampling Station Location

type function

down

which

i n t o three m a j o r

206

3.

Sampling Frequency The

term

water

quality

variable

is

used

instead

of

water

quality

parameter because water q u a l i t y i s a random v a r i a b l e a n d c a n be d e f i n e d by

statistical

addition,

parameters

the term

deterministic

parameter

equations

a s the mean a n d

such or

is

most

models

often

and

standard

used

to

can

lead

it

deviation.

define

In

constants confusion

to

of by

i d e n t i f y i n g i t a s a random v a r i a b l e . the

monitoring

system's o p e r a t i o n a l f u n c t i o n s I i s t e d p r e v i o u s l y a n d v i c e versa.

Each

of

these

factors

The degree

of impact, however,

in

network

design

effects

all

depends upon the purpose a n d g o a l s of

the m o n i t o r i n g

system. SELECT ION OF WATER QUALITY VARIABLES TO MEASURE

to

The selection of the water q u a l i t y

v a r i a b l e to be sampled w i l l

a

of

l a r g e extent

background developing network

frame

the of

its

objectives reference

the o b j e c t i v e s

has

stndards, for

or

on

of

primary

the

of

the

sampling

the

individuals

monitoring

objective

to

network

network.

monitor

the

responsible

for

When

a

compliance

sampl i n g

with

stream

the v a r i a b l e s sampled a r e the ones s p e c i f i e d i n the l e g i s l a t i o n ,

example,

dissolved

(DO).

oxygen

DO

is

sampled

because

s t a n d a r d s specify a minimum l e v e l which should not be v i o l a t e d . s t a n d a r d l e g i s l a t i o n were those r e l a t e d to water s u p p l y , biochemical oxygen demand a n d dissolved solids,

(BOD),

stream

Dissolved

i m p o r t a n t a n d i n c l u d e d in stream

oxygen a n d o t h e r v a r i a b l e s deemed most

quality

depend

and

temperature,

col iform b a c t e r i a ,

turbidity,

and

suspended

because most i n d i v i d u a l s e n t e r i n g the f i e l d o f water

management d u r i n g

the

last

few

decades

have

a

background

in

s a n i t a r y engineering. Since i n d i v i d u a l s o t h e r t h a n besides s a n i t a r y became interested i n water q u a l i t y , which

should

be

sampled

( e n v i r o n m e n t a l ) engineers

the number of water

routinely

has

increased.

quality This

variables

compounding

syndrome cannot a n d should not be the major v a r i a b l e selection mode f o r a permanent,

routine

accommodated

in

sampling

the

p o p u l a r i t y of synoptic

much

program,

discussed

but

instead

synoptic

can

surveys.

be

The

easily

increasing

s u r v e y s w i t h s a m p l i n g agencies i s p r o b a b l y

due to

the f a c t t h a t the s u r v e y s a r e in fact a n a p p l i c a t i o n of a systems a p p r o a c h to

water

programs, sampling

quality

monitoring.

the objectives, frequency,

the

Unlike

the

permanent,

the use of the d a t a , variables

to

be

routine

the s a m p l i n g

sampled

as

well

sampling

locations, as

the

the data

207 analysis

procedures

and

decisions

to

be

made

should

be

developed

be

developed

completely before the survey i s undertaken. Both

sampling

independently

location

of

the

and

water

sampling

quality

frequency

variable

to

can

be

analyzed,

location and frequency a r e specified f o r the c o l l e c t i o n of ( t h e analyses a r e made l a t e r ) .

However,

water

monitored.

quality

week

at

a

monitoring

variable

single the

being

point

in

relatively

a

river

stable

For

may

river

the

variables

t h e i r n a t u r a l and/or

considered

when

be

more

temperature, coliform

sampling than

but

once

adequate

may

bacteria

water

delineated.

Network

concentration

qua1 i t y

is

concentration,

the

as

former

be

sample

in

if

opposed

being

a

to

an

result

24-hour

(generally

daily

in

space

In

several

period,

while

the daytime,

in a be to

should

be

(flow

weighted)

grab

samples the

can

addition

units

mean

instantaneous

of

for

hardly

be s p e c i f i e d so

time a n d

respective

a

a

concentrations.

should

network.

their

differs

measurements spaced d u r i n g a single

variation

monitoring

variables,

design

needed

the

to be monitored

man-made

designing

considering

only a

example,

before a water q u a l i t y m o n i t o r i n g network can be designed

systematic fashion, that

both

both c r i t e r i a a r e affected b y the

adequate for m o n i t o r i n g r a p i d l y v a r y i n g Therefore,

as

the water sample

sample

with

latter

flow

comprises a.m.

between 8.00

and

4.30 p.m.1. In

reality,

the

specification

of

the

water

quality

variable

however, water

to

be

In p r a c t i c e ,

monitored p r i o r to i n i t i a t i n g network design would be ideal.

network design i s specified a n d one must know o r determine what

quality

variables

can

be

accurately

monitored

with

the

existing

a

water’

network.

SAMPL I NG STAT ION LOCAT ION The

location

of

m o n i t o r i n g network design,

a

permanent

i s probably

b u t a l l too often

never

comprises lead i n many cases r i v e r g a u g i n g stations. the

gauging

sampled

is

collectors

station not

and

follow

when

most

properly

is

truly

addressed.

representative generally

of

the

water

the

in

aspect

of

quality

the

Expediency

network a n d cost

near existing

Whether the s i n g l e g r a b sample from the b r i d g e o r but

users

station

critical

to s a m p l i n g from b r i d g e s o r

known,

e s t i m a t i n g discharge, indicate exactly

sampling

the

is

quality

of

the

assumed data.

measuring

discharge.

water

quality

However, variable

be

Using

measurement anywhere i n the river

water to

lateral

t h i s does

mass

being

by

both

the

river

stage

for

transect not

would

necessarily

concentrations.

In

fact

208

F i g , 13.1

Macrolocation of Sampling Stations W i t h i n a R i v e r Basin Using the Percent Areal Coverage a s the C r i t e r i a S p e c i f y i n g Locat ion

209 research

indicates

the

opposite,

that

will

rarely

a

single

sample

be

i n d i c a t i v e of the average water q u a l i t y i n a r i v e r cross section. Sampling

locations

for

a

c l a s s i f i e d i n t o two levels of

permanent design:

water

quality

network

former

b e i n g a f u n c t i o n o f the specific objectives o f the network

latter

being

independent

of

can

be

macrolocation a n d microlocation,

the

objectives

but

a

the

and

the

of

the

function

representativeness of the water sample to be collected. The political etc.

macrolocation

within

boundaries,

a r e a s of

Macrolocation can

a

river

basin

usually

major p o l l u t i o n

be specified,

coverage u s i n g b a s i n c e n t r o i d s

a s well,

(Sanders et

is

loads,

determined

population

a c c o r d i n g to percent

1986).

al,

This

locates sampling p o i n t s in a systematic f a s h i o n m a x i m i z i n g the e n t i r e b a s i n w i t h a few s t r a t e g i c a l l y an

example

of

locating

sampling

using

areal

methodology

information of F i g u r e 13.1

located stations.

stations

by

centres,

basin

centroids

is and

sub-basin centroids w i t h percent a r e a l coverage a s the c r i t e r i a . The procedure f o r l o c a t i n g sampling s t a t i o n s i s d e r i v e d b y d e t e r m i n i n g the c e n t r o i d o f a r i v e r system. i s a stream

without

defined

i n t e r i o r stream r e s u l t i n g from

value

equal

to

the

i s given

intersection

of

the v a l u e o f two e x t e r i o r

(this

one;

an

tributaries

Continuing downstream i n the same manner,

would have a v a l u e of two. streams intersect,

Each c o n t r i b u t i n g e x t e r i o r t r i b u t a r y

tributaries)

as

the r e s u l t a n t downstream s t r e t c h of r i v e r would h a v e a the

sum

of

the

values

of

the

preceeding

intersecting

stream. At the mouth of the r i v e r , the v a l u e o f the f i n a l r i v e r section w i l l be equal to the number o f c o n t r i b u t i n g e x t e r i o r t r i b u t a r i e s ,

22 in F i g u r e

13.1.

by

D i v i d i n g the

v a l u e of

the f i n a l

v a l u e of the c e n t r o i d of the b a s i n ,

s t r e t c h of

1 1 i s calculated.

h a v i n g a v a l u e equal to t h a t of the c e n t r o i d sections and

i s the

location of

the

the

river

r i v e r basin, of

I n many

sampling station

cases,

when

with

When

this

occurs,

closest to the c e n t r o i d i s chosen.

the

stream

highest

the

initial

river

basin

centroid.

segment

having

the two equal The

two

order

the mouth

t h i s procedure to

The n e x t o r d e r o f sampling

determined b y f i n d i n g the c e n t r o i d v a l u e of a n d below

applying

into

there i s u s u a l l y not a stream h a v i n g a v a l u e e q u a l to

the centroid.

the

The section of r i v e r

d i v i d e s the b a s i n

( t h e assumption i s made t h a t there e x i s t s a s a m p l i n g s t a t i o n a t of the r i v e r b a s i n ) .

two,

a

a

that value

locations

is

sections above

procedure

is

continued

u n t i l a percentage of a r e a l coverage i s a t t a i n e d . The percentage of area coverage specified b y the m o n i t o r i n g agency defined as the number of

sampling

the

this

basin.

sampling

Intrinsic

in

station hierarchy

stations d i v i d e d b y

objective

that

procedure

o r d e r s the

is

importance

is

the m a g n i t u d e of the of

concept each

of

a

sampling

210 station

in the b a s i n

1973). T h i s p r o v i d e s a

(Sharp,

r e a l i s t i c methodology

i n which a r a t i o n a l implementation progam c a n proceed: stations

(highest

available,

order)

additional

are

built

first

and

as

the most

the

important

resources

become

As each succeeding h i e r a r c h y

s t a t i o n s can be b u i l t .

of s t a t i o n s a r e e s t a b l i s h e d the percentage of a r e a l coverage i s increased. Having

established

microlocation

the

specifies

macrolocations

the

river

within

reach

to

a

be

river sampled

microlocation specifies the p o i n t i n the r e a c h to be sampled.

basin,

the

while

the

This point

is

t h e location of a zone in the r i v e r r e a c h where complete m i x i n g e x i s t s a n d

in o r d e r to o b t a i n a

o n l y one sample i s r e q u i r e d from the l a t e r a l transect

(in

representative

space)

sample.

Being

downstream from the nearest o u t f a l l ,

a

function

t h e zone of

of

the

distance

complete m i x i n g can

be

estimated u s i n g v a r i o u s methodologies. Given the assumptions t h a t a p o i n t

source

stream approximates a Gaussian d i s t r i b u t i o n , modelled

using

image

theory,

in a

d i s t a n c e downstream

the

following

straight,

pollutant

a n d t h a t b o u n d a r i e s can equation

u n i f o r m channel

-

-

(J

Y

where

a point

L

Y

be the

source

1977).

2u

(13.1) is

the

from

mixing

source

velocity and D Estimates of D

Y

predict

2oy

distance

D

can

from

p o l l u t a n t to a zone of complete m i x i n g (Sanders et a l . ,

LY

in a

distribution

Y

Y

to

distance farthest

for

complete

lateral

lateral

boundary,

u

mixing,

a y

is

stream

mean

is

i s the l a t e r a l t u r b u l e n t d i f f u s i o n coefficient. can be made u s i n g e q u a t i o n 13.2

= 0.23 du'

(13.2)

where d i s depth of flow u* i s shear v e l o c i t y

g

i s acceleration flow

due to g r a v i t y R i s h y d r a u l i c r a d i u s S i s slope o r t h e h y d r a u l i c g r a d i e n t (Sanders e t al., Unfortunately,

1977). there may not e x i s t

in a g i v e n r i v e r

of complete m i x i n g due i n p a r t to the random n a t u r e of

mixing

distance,

determination of

inapplicability

of

the m i x i n g distance,

the

assumptions

o r more often

river

l e n g t h o r t u r b u l e n c e to assure complete m i x i n g

river

reach.

On

the o t h e r

hand field

reach any

within

in

used

t h a n not,

v e r i f i c a t i o n of

points

the aforementioned not

the

enough

the s p e c i f i e d

a completely

mixed

zone p r i o r to l o c a t i n g a permanent s a m p l i n g s t a t i o n c a n be e a s i l y done b y collecting

m u l t i p l e samples

in the cross

u s i n g a we1 I-known one- o r two-way

section

and analyzing

the

a n a l y s i s of v a r i a n c e techniques.

data

21 1 If

there

sampled,

is

not

a

completely

mixed

zone

the

in

river

reach

to

be

there a r e three a l t e r n a t i v e s :

( 1 ) Sample anyway a t a s i n g l e p o i n t a n d assume i t i s r e p r e s e n t a t i v e ( t h i s i s a general approach adopted t o d a y ) ;

( 2 ) Don't sample the r i v e r reach a t a l l , obtained does not q u a l i t y o f the

represent

sample

because t h e d a t a w h i c h would be

the e x i s t i n g r i v e r

quality,

b u t only

In o t h e r words,

volume collected.

the

the data

is

useless;

( 3 ) Sample a t several p o i n t s in the l a t e r a l transect c o l l e c t i n g a composite mean, which would be r e p r e s e n t a t i v e of the water q u a l i t y

in the r i v e r

a t that p o i n t i n time a n d space.

I f the sample i s not r e p r e s e n t a t i v e of the water mass, sampling

as

presentation

well and

as the

the

mode

realistic

m a k i n g becomes inconsequential.

of

use

data of

analysis,

the

data

interpretation

for

I n s p i t e of t h i s f a c t ,

the frequency of

objective

and

decision

c r i t e r i a to e s t a b l i s h

s t a t i o n locations f o r r e p r e s e n t a t i v e s a m p l i n g h a v e received r e l a t i v e l y

little

a t t e n t i o n from many i n s t i t u t i o n s a n d agencies responsible f o r water q u a l i t y monitoring. SAMPLING FREQUENCY Once sampling

stations

a r e representative

have been

i n space,

located to ensure

sampling

frequency

samples collected

should

be

specified

so

t h a t the samples a r e r e p r e s e n t a t i v e in time. Sampling frequency basin

is

a

very

a t each permanent

important

parameter

sampling station w i t h i n a

which

must

be

considered

design of a water q u a l i t y m o n i t o r i n g network.

A l a r g e p o r t i o n of

o f o p e r a t i n g a m o n i t o r i n g network

r e l a t e d to

sampling.

However,

the

reliability

d e r i v e d from a m o n i t o r i n g network sampling.

Addressing

is directly

this

and

utility

of

river in

the

the costs

the frequency

water

quality

of

data

i s l i k e w i s e r e l a t e d to the frequency of

anomaly

Quimpo

(1968)

summarized

the

s i g n i f i c a n c e of sampling frequency a n d stated t h a t : On the one hand,

b y s a m p l i n g too often,

obtained i s r e d u n d a n t and t h u s expensive, hand,

the i n f o r m a t i o n a n d on the other

sampling too i n f r e q u e n t l y bypasses some i n f o r m a t i o n

necessitating an extended p e r i o d of observation. Significant v i o l a t ion

,

as

sampling

frequency

is

m a i n t a i n i n g e f f I uent standards,

i n ambient water q u a l i t y ,

very

to

detecting

stream

standards

a n d e s t i m a t i n g temporal changes

l i t t l e q u a n t i t a t i v e c r i t e r i a which designate

a p p r o p r i a t e sampling frequencies h a v e been a p p l i e d to the design of water

21 2 quality

monitoring

networks.

many

In

cases,

professional

judgment

cost c o n s t r a i n t s p r o v i d e the b a s i s f o r s a m p l i n g frequencies.

All

frequencies

upon

are

capabilities, only

the

same

at

once-a-month,

practical

means

each

station

once-a-week,

to

implement

etc.

a

frequencies

as

and

1978).

Adrian,

functions

of

the

variable

(Nyquist frequency),

maximum

to

minimum

flow

cyclic

methods

variations

and

(Ward et

possibly

the

considering

the

include

of

the

b a s i n area

water

and

19671,

Orlob,

specifying

of

a

test

measuring

the

confidence

1976; L o f t i s a n d Ward,

al,

water

quality

the r a t i o of

quality

intervention

1978),

1978), and

the number of d a t a p e r y e a r f o r hypotheses (Sanders and Ward, the power

routing

s a m p l i n g frequencies a t each

The

the d r a i n a g e

(Pomeroy

i n t e r v a l o f the a n n u a l mean

although

program

too often,

there do e x i s t many q u a n t i t a t i v e ,

s t a t i s t i c a l l y meaningful procedures to specify (Sanders

based

and

sampl i n g

s t a t i s t i c a l b a c k g r o u n d o f d a t a collectors, station

and

and

(Lettenmaier,

1975).

A l l of the aforementioned procedures can b e a p p l i e d to the design of a water q u a l i t y m o n i t o r i n g network w i t h each r e q u i r i n g a d i f f e r e n t statistical

sophistication

assumptions app I y One of variable

the

.

simplest

(iid)

and

as

approaches

concentrations

distributed

insofar

are

is

data

to assume

random,

determine

the

requirements that

the

independent

number

of

as

well

water

and

samples

level of as

quality

identically

per

year

as

a

f u n c t i o n o f an a l l o w a b l e ( s p e c i f i e d ) confidence i n t e r v a l of the mean a n n u a l concentration analyses of

( t h i s i s analogous to the procedure f o r d e t e r m i n i n g how many a

water

sample

should

be

made

to

determine

a

reasonable

estimate o f the mean water q u a l i t y v a r i a b l e c o n c e n t r a t i o n ) .

[

n =

aizS]

(13.3)

where n i s the number of e q u a l l y is a

constant

number

of

which

samples,

is a

S

is

spaced samples collected p e r y e a r ,

function the

of

the

standard

l e v e l of

deviation

concentrations a n d R i s s p e c i f i e d h a l f - w i d t h

of

significance of

the

water

the confidence

taI2

and

the

quality

interval

of

the a n n u a l mean. Using the same assumption,

t h a t the water

number of samples p e r

year

can

a n a l y s i s procedure as

well.

For

quality

be s p e c i f i e d a s a example,

if

variable i s iid, function

annual

of

means

tested f o r s i g n i f i c a n t changes u s i n g the d i f f e r e n c e in means,

the

the data

were

to

be

then to detect

a n assumed level of change, t h e number of samples c a n be specified.

A

more

sophisticated

procedure,

representing

a

higher

level

of

21 3

0.9

0.8

R vs. Number of Somples per Yeor I 2 3 4 5 6 7 8

0.7

0.6

Wore Conn. at Thompsonville Deerfield Conn. ot Montopue City Millers Conn.ot Vernon

Westfield Conn. ot Turners Falls

R

0.5

0.4

0.3

0.2

0. I

I

10

1

20

I

30

I

40

I

50

Number of Somples per Yeor

Fig 13.2

A p l o t n u m b e r o f s a m p l e s per y e a r of the expected h a l f - w i d t h of t h e c o n f i d e n c e i n t e r v a l of m e a n log f l o w , R , v e r s u s n u m b e r of S a m p l e s for S e v e r a l R i v e r s in t h e C o n n e c t i c u t R i v e r B a s i n

214 statistical

analysis,

may not be i i d ,

would

be

to recognize

b u t h i g h l y dependent,

that

water

seasonal v a r i a t i o n ,

a n d determine s a m p l i n g frequency

variability

water

of

the

quality

p e r i o d i c components h a v e daily

discharge,

data

been

variable

removed.

bases

of

quality

veriables

not i d e n t i c a l l y d i s t r i b u t e d ,

as a f u n c t i o n of

series

after

trend

Unfortunately,

other

than

water

time

having

quality

number, r e l i a b i l i t y a n d l e n g t h a r e g e n e r a l l y

variable

of

the and

mean

sufficient

not a v a i l a b l e f o r a p p l i c a t i o n

of t h i s procedure. Once utilized quality

a

uniform

to

objectively interval

frequencies)

of

the of

where

Thus,

stations

sampled

more

frequently

little.

With

number

reference

of

of

sampling

annual

equality

station.

these

samples

per

13.2

the

(for

it

can

within

a

varies

where which

of

specifying

in a

the is

mean

number

at

water

a

of

fashion sampling

tremendously plot

of

samples

will

quality

log r i v e r

the

flow

the

sampling

each

water

be

of

consistent

half-widths

quality

interval

year,

frequencies

mean

stations

selected

the expected h a l f - w i d t h

expected

Figure

the confidence

is

basin-wide

water

than

to

criterion

For example,

approach c a n be a p p l i e d

specifying

half-width

frequency

distribute

m o n i t o r i n g network.

confidence by

sampling

be

varies expected

versus

collected

at

the each

s t a t i o n w i t h i n the r i v e r b a s i n f o r a g i v e n R a r e determined b y d r a w i n g a horizontal abscissa curve.

line axis

through below

Figure

13.2

and

R

the

may

reading

intersections also

the

on

be used

number

the

i n an

of

samples

horizontal

line

i t e r a t i v e fashion

on

with to

the each

specify

s a m p l i n g frequencies a t each s t a t i o n when a t o t a l number o f samples from the b a s i n

i s specified.

For example,

collected a n d analyzed, horizontally;

a

v a l u e of

the number of

if

R

only

samples s p e c i f i e d

curves a r e summed a n d compared

to

N

samples

i s assumed

N.

If

the

by

and the

sum

a

per

year

line

is

were drawn

i n t e r s e c t i o n of

were not e q u a l

the to N

then another estimate of R would be made u n t i l the sum of a l l the samples i s equal to N. I t should be noted t h a t the expected h a l f - w i d t h o f the a n n u a l mean i s not the o n l y s t a t i s t i c

that

the expected h a l f - w i d t h a n d may

can

be used

to

specify

s a m p l i n g frequencies;

d i v i d e d b y the mean i s a measure o f r e l a t i v e e r r o r

be more a p p r o p r i a t e

when

assigning

sampling

frequencies

in

a

b a s i n where water q u a l i t y v a r i e s tremendously from r i v e r to r i v e r . When developing s a m p l i n g frequencies, important

cycles

concentrations,

which

can

have

one must keep i n m i n d two v e r y

immense

impact

on

the d i u r n a l c y c l e a n d the weekly cycle.

d i u r n a l cycle (which i s a

f u n c t i o n of

the r o t a t i o n

e l i m i n a t e d b y s a m p l i n g in e q u a l time i n t e r v a l s f o r

of a

water

The effect the e a r t h )

24-hour

quality of can

period

the be and

215 the effect of t h e weekly c y c l e ( w h i c h i s a f u n c t i o n of mans' be eliminated be m u l t i p l e s

by specifying of

seven,

that

and

sampling

occasional

i n t e r v a l s for a

sampling

on

a c t i v i t y ) can

network

weekends

cannot

would

be

necessary.

in terms of v a r i a b l e s

Perhaps the major impact between network design to

monitored,

be

operational

sampling

monitoring

consequently,

location,

functions

ultimate

v a l u e of

sampling program that

is

and

the

sampling

the

in

area

monitoring

frequency

of

data

network

and

the

analysis

and,

information.

Any

i s to generate conclusive r e s u l t s from o b s e r v i n g

stochastic process ( w a t e r q u a l i t y concentrations) must be well s t a t i s t i c a l l y designed.

S t a t i s t i c a l l y designed

implies

p l a n n e d ( i n p r o p e r locations and numbers) so t h a t

that

a

planned and

the

sampling

the s t a t i s t i c a l

techniques chosen w i l l be a b l e to y i e l d q u a n t i t a t i v e information.

is

analysis Thus,

the

d a t a a n a l y s i s techniques ( l e v e l and t y p e of s t a t i s t i c s ) to be used must be defined

in

order

to

know

how

to

compute

proper

sampling

frequencies,

locations, etc.

D ISCUSS ION The above section has pointed out many problems due to not d e s i g n i n g a m o n i t o r i n g system that

all

accuracy. on

aspects

in a

of

For example,

nonrepresentative,

excessive segment

.

a

accuracy

context.

Perhaps

program

i n one

sample d a t a . segment

The

compared

the major

should

i t would not be wise to

grab

I n a s i m i l a r manner, sophisticated

systems

monitoring

match

use

time

system to

concern

in

terms

series

would

be

the accuracy

analysis providing another

in

i t may be u n r e a l i s t i c to encourage use of

sample collection

and

laboratory

is of

a n a l y s i s techniques

more

if

the

d a t a i s not to receive a thorough s t a t i s t i c a l a n a l y s i s . It

i s difficult

to

test

hypotheses,

make decisions

flow

weighted,

several

times

a

year,

from

and

i n i t i a t e action

in the daytime a n d not

u s i n g water q u a l i t y d a t a which a r e collected o n l y

locations

which

are

not

completely mixed a n d u s i n g l a b analyses procedures which may h a v e more variation

in

their

results

when

analyzing

the

same

sample

than

the

ambiant v a r i a t i o n of the water q u a l i t y v a r i a b l e in the r i v e r . Perhaps an even l a r g e r concern to those in m o n i t o r i n g network i s the

use of

water

quality

T h i s lowers the v a l u e of a n y t h a t of spot checks. standards

would

standards information

that

generally

ignore

design

statistics.

from a compliance v i e w p o i n t ,

I n c o r p o r a t i n g water q u a l i t y means a n d v a r i a t i o n

greatly

facilitate

incorporating

more

statistics

to into into

216 m o n i t o r i n g . T h i s would h a v e t h e effect of t y i n g network design to d a t a use in a much more concrete,

a l s o encourage use of would

be

a

s t a t i s t i c a l manner t h a n i s now possible.

the

statistical

system

thread

approach moving

to

network

through

the

design entire

I t would as

there

monitoring

operat ion.

REFERENCES Lettenmaier, D.P., 1975. Design of M o n i t o r i n g Systems f o r Detection of Trends i n Stream Q u a l i t y . Technical Report No. 39, Charles W. H a r r i s H y d r a u l i c s L a b o r a t o r y , U n i v e r s i t y of Washington, Seattle. L o f t i s , J.C. a n d Ward, R.C., 1978. S t a t i s t i c a l Tradeoffs i n M o n i t o r i n g Network Design, presented a t AWRA Symposium Establishment of Water Q u a l i t y M o n i t o r i n g Programs. San Francisco, C a l i f o r n i a . a n d Orlob, G.T., 1967. Problems of S e t t i n g S t a n d a r d s o f Pomeroy, R.D. S u r v e i l l a n c e f o r Water Q u a l i t y Control. C a l i f o r n i a State Water Q u a l i t y Control Board P u b l i c a t i o n No. 65, Sacramento, C a l i f o r n i a . 1968. Stochastic A n a l y s i s of D a i l y R i v e r Flows. Journal o f Quimpo, R.G., H y d r a u l i c s , ASCE. 94(HY1) p43-47. A d r i a n , D.D. a n d Joyce, J.M., 1977. M i x i n g L e n g t h f o r Sanders, T.G., Representative Water Q u a l i t y Sampling. Journal Water P o l l u t i o n Control Federation. 49 p2467-2478. T.G. a n d Ward, R.C., 1978. R e l a t i n g Stream Standards to Sanders. Regulatory Water Q u a l i t y M o n i t o r i n g Practices. Presented a t the AWRA Symposium “Establishment of Water Q u a l i t y M o n i t o r i n g Programs, San Francisco, Ca I i f o r n i a . and Adrian, D.D., 1978. Sampling Frequency f o r R i v e r Sanders, T.G. Q u a l i t y M o n i t o r i n g . Water Resources Research. 1 4 ( 4 ) p 569-576. Ward, R.L. L o f t i s , J.G. Steel, T.D, Adrian, D.D. and Sanders, T.G., 1986. Design of Networks f o r M o n i t o r i n g Water Q u a l i t y , Yevjevich, V., 2nd E d i t i o n , Water Resources P u b l i c a t i o n s , Colorado. Sharp, W.E., 1973. A T o p o l o g i c a l l y Optimum R i v e r Sampling P l a n f o r South C a r o l i n a . Water Resources Research I n s t i t u t e Report No. 36, Clemson U n i v e r s i t y , Clemson , South Carol i n a . Neilsen, K.S. a n d Bundgaard-Nielsen, M., 1976. Design of Ward, R.C., M o n i t o r i n g Systems f o r Water Q u a l i t y Management. C o n t r i b u t i o n f o r the Water Q u a l i t y I n s t i t u t e , Danish Academy of Technical Science, No. 3, Horshdm, Denmark.